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Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
23rd Biennial Conference of the International Telecommunications Society (ITS): "Digital societies and industrial transformations: Policies, markets, and technologies in a post-Covid world", Online Conference / Gothenburg, Sweden, 21st-23rd June, 2021
Verlag: 
International Telecommunications Society (ITS), Calgary
Zusammenfassung: 
Based on a unique and exhaustive database, including micro-level cross-sectional data on 23 million observations over nine years, from 2009 to 2017, we assess whether broadband quality has an impact on income and unemployment reduction. Overall, the results do not show any significant effect of download speed on either income or the unemployment rate. However, after distinguishing between educational attainment and the city size, we obtained heterogeneous results. While we highlight a substitution effect between low-skilled workers and broadband in smaller cities, we also show that broadband quality has a positive impact on unemployment reduction for low-skilled workers in bigger cities. However, the model predicts a negative effect of broadband quality on both the median income and the unemployment rate in areas having a higher proportion of college graduates. This result tends to support the analyses showing that, with the progress made in machine learning, artificial intelligence and the increasing availability of big data, job computerization is expanding to the sphere of high-income cognitive jobs.
Schlagwörter: 
Broadband Quality
Fibre
Income
Unemployment
Artificial Intelligence
JEL: 
L13
L50
L96
Dokumentart: 
Conference Paper

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